Lateral coherence in isotropic turbulence and in the natural wind

Kristensen, Leif; Jensen, N.O.

doi:10.1007/bf00117924

Cited by 109 publications

(71 citation statements)

References 14 publications

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“…The relatively low number of data points with significantly high coherence leads to some uncertainties regarding the parameter c 2 . A coherence lower than 1 at zero frequency may be expected for large lateral separations [27], which would correspond to a value of c 2 between 0.01 s −1 and 0.2 s −1 as observed in the Lysefjord [54]. In the present case, the coefficient c 1 is the same as the decay coefficient C y u of the Davenport coherence model because the value of c 2 is close to 0 s −1 .…”

Section: Lateral Coherence Of the Longitudinal Wind Fluctuationssupporting

confidence: 65%

“…Decay coefficients provided by the Handbook N400 [9] for the coherence model in Equation (14). For a large crosswind separation d y , the ratio d y /L (where L is a typical length scale of the turbulence) cannot be considered small and the coherence becomes less than unity at zero frequency [27]. This is not accounted for in the Davenport coherence model, which results in an overestimation of the fitted decay coefficient.…”

Section: The Wind Coherencementioning

confidence: 99%

“…• Ropelewski et al [49], Kristensen and Jensen [27] or Sacré and Delaunay [39] observed that C y u decreases for increasing heights. It is, therefore, not surprising if the lateral co-coherence estimated at z = 25 m is lower than the one at z = 60 m, as measured by Jensen and Hjorth-Hansen [53].…”

mentioning

confidence: 98%

“…That is one of the reasons why Kristensen and Jensen [27] considered only relatively small lateral separations. If a coherence model with a single parameter is used, the decay coefficient may increase for increasing cross-wind separations, especially in stable or near-neutral atmosphere [61,64].…”

mentioning

confidence: 99%

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Measurements of Surface-Layer Turbulence in a Wide Norwegian Fjord Using Synchronized Long-Range Doppler Wind Lidars

et al. 2017

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Three synchronized pulsed Doppler wind lidars were deployed from May 2016 to June 2016 on the shores of a wide Norwegian fjord called Bjørnafjord to study the wind characteristics at the proposed location of a planned bridge. The purpose was to investigate the potential of using lidars to gather information on turbulence characteristics in the middle of a wide fjord. The study includes the analysis of the single-point and two-point statistics of wind turbulence, which are of major interest to estimate dynamic wind loads on structures. The horizontal wind components were measured by the intersecting scanning beams, along a line located 25 m above the sea surface, at scanning distances up to 4.6 km. For a mean wind velocity above 8 m·s −1 , the recorded turbulence intensity was below 0.06 on average. Even though the along-beam spatial averaging leads to an underestimated turbulence intensity, such a value indicates a roughness length much lower than provided in the European standard EN 1991-1-4:2005. The normalized spectrum of the along-wind component was compared to the one provided by the Norwegian Petroleum Industry Standard and the Norwegian Handbook for bridge design N400. A good overall agreement was observed for wave-numbers below 0.02 m −1 . The along-beam spatial averaging in the adopted set-up prevented a more detailed comparison at larger wave-numbers, which challenges the study of wind turbulence at scanning distances of several kilometres. The results presented illustrate the need to complement lidar data with point-measurement to reduce the uncertainties linked to the atmospheric stability and the spatial averaging of the lidar probe volume. The measured lateral coherence was associated with a decay coefficient larger than expected for the along-wind component, with a value around 21 for a mean wind velocity bounded between 10 m·s −1 and 14 m·s −1 , which may be related to a stable atmospheric stratification.

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Section: Lateral Coherence Of the Longitudinal Wind Fluctuationssupporting

confidence: 65%

Section: The Wind Coherencementioning

confidence: 99%

mentioning

confidence: 98%

mentioning

confidence: 99%

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Measurements of Surface-Layer Turbulence in a Wide Norwegian Fjord Using Synchronized Long-Range Doppler Wind Lidars

et al. 2017

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“…The flow field characteristics of doubly-fed wind farm also were studied using CFD software in complex terrain in [6][7][8], and the main purpose of the study is to comprehend the turbulence characteristics of doubly-fed wind farm. In order to study the randomness and turbulence characteristics of wind speed, the spectrums of the randomness wind speed is analyzed from the perspective of the frequency domain, and the correlation function is used to describe the turbulence effects between different positions in flow field [9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Calculation Method of Instantaneous Wind Speed Spatial Distribution of Wind Farm

Hui

et al. 2015

Int. J. Onl. Eng.

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Abstract-Instantaneous wind speed spatial distribution of wind farm is the basis of the optimal control for wind turbines. A calculation method was proposed for the instantaneous wind speed spatial distribution in wind farm, which made the instantaneous wind speed spatial distribution is divided into wake and non-wake zone. For the non-wake zone, the instantaneous wind speed spatial distribution is mainly affected by the flow field coupling between wind turbines, in order to describe the influence accurately, a cross spectral matrix was constructed including the wind turbine mutual distance and the azimuth in wind farm, and the solving calculation process of the cross spectral matrix was deduced. For the wake zone, single wind turbine wake model and wake superposition model were established according to conservation of momentum, and then the average wind speed spatial distribution in wake zone was calculated. According to the average wind speed spatial distribution, the instantaneous wind speed spatial distribution was calculated. A wind farm is selected as case to verify the calculation method, and the results show that this calculation method can accurately describe the instantaneous wind speed spatial distribution of wind farm.

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Wind power meteorology. Part I: climate and turbulence

Petersen¹,

Mortensen²,

Landberg³

et al. 1998

Wind Energ.

116

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Wind power meteorology has evolved as an applied science firmly founded on boundary layer meteorology but with strong links to climatology and geography. It concerns itself with three main areas: siting of wind turbines, regional wind resource assessment and short‐term prediction of the wind resource. The history, status and perspectives of wind power meteorology are presented, with emphasis on physical considerations and on its practical application. Following a global view of the wind resource, the elements of boundary layer meteorology which are most important for wind energy are reviewed: wind profiles and shear, turbulence and gust, and extreme winds. Copyright © 1998 John Wiley & Sons, Ltd.

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Lateral coherence in isotropic turbulence and in the natural wind

Cited by 109 publications

References 14 publications

Measurements of Surface-Layer Turbulence in a Wide Norwegian Fjord Using Synchronized Long-Range Doppler Wind Lidars

Measurements of Surface-Layer Turbulence in a Wide Norwegian Fjord Using Synchronized Long-Range Doppler Wind Lidars

Calculation Method of Instantaneous Wind Speed Spatial Distribution of Wind Farm

Wind power meteorology. Part I: climate and turbulence

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